AI Infrastructure Architect Intern

Intel Corporation; Santa Clara, Northern (CA, KY); Hybrid; USD 133,000 - 134,000; Part time

Benefits offered by this job

Stock bonuses

Health benefits

Retirement plan

Vacation

Job summary

Intel Corporation in Santa Clara, CA seeks an AI Infrastructure Solution Architect Intern to join the AI Platforms team. You will work with experienced engineers to deploy AI accelerator systems, validate multi-node clusters, and benchmark AI workloads, gaining hands-on exposure to AI infrastructure and system software.

The role emphasizes Linux, computer architecture, and building end-to-end AI solutions with a focus on automation, debugging, and performance optimization.

Qualifications

• Pursuing a Master's in CS/CE/EE/DS/AI or related field.
• Strong Python programming and Linux command line skills.
• Understanding of computer architecture, OS, networking, or distributed systems.
• Demonstrated problem-solving through coursework, projects, or internships.

Responsibilities

• Assist in deploying and validating AI accelerator systems and multi-node AI clusters.
• Support cluster bring-up activities, including provisioning, software installation, and health verification.
• Execute performance benchmarks and collect system telemetry.
• Troubleshoot system, networking, and software issues in AI environments.
• Develop Python-based automation tools for testing, monitoring, and data collection.
• Participate in end-to-end AI solution development with cross-functional teams.

Skills

Python programming

Linux

Computer architecture

Distributed systems

Analytical thinking

Team collaboration

Education

Master's degree in Computer Science/Engineering/Data Science/AI or related fields

Tools

Python

C/C++

Bash scripting

Git

Docker

PyTorch

TensorFlow

Job description

Intel Corporation in Santa Clara, CA seeks an AI Infrastructure Solution Architect Intern to join the AI Platforms team. You will work with experienced engineers to deploy AI accelerator systems, validate multi-node clusters, and benchmark AI workloads, gaining hands-on exposure to AI infrastructure and system software.

The role emphasizes Linux, computer architecture, and building end-to-end AI solutions with a focus on automation, debugging, and performance optimization.